Factors influencing adoption of crossbred cattle in different agro-ecological zones of Bangladesh by M. A. Quddus

“…Thus, the research investigates the demographic, socioeconomic and agro-ecological factors and farming assets and facilities of the small farm holders that influence the adoption of crossbreds. Multistage random sampling technique was used to random selection of 300 cattle households in four agro-ecological zones. …”
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Spatial distribution and determinants of saving habit and ownership of asset among households in Ethiopia: evidence from living standards measurement study 2018/19 data by Birhan Walie Alamneh, Demeke Lakew Workie, Teshager Assefa Sisha, Dereje Tesfaye Zekie, Getachew Abate Dagnew

“…Methods In this study, the data were taken from the Living Standards Measurement Study 2018/19. 5650 households were selected by using a two-stage stratified random sampling technique. Spatial distribution, separate, and bivariate binary logistic regression analyses were applied. …”
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Associative Hypercomplex Algebras Arise over a Basic Set of Subgeometric One-Dimensional Elements by Alexander P. Yefremov

“…An abstract set of one-dimensional (spinor-type) elements randomly oriented on a plane is introduced as a basic subgeometric object. …”
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Robust Fault-Tolerant Control for Uncertain Networked Control Systems with State-Delay and Random Data Packet Dropout by Xiaomei Qi, Chengjin Zhang, Jason Gu

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Machine learning approach for differentiating iron deficiency anemia and thalassemia using random forest and gradient boosting algorithms by Wanicha Tepakhan, Wisarut Srisintorn, Tipparat Penglong, Pirun Saelue

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Random Access Optimization With Generative Adversarial Networks in Industrial IoT Using Deep Deterministic Policy Gradient Approach by Ishtiaq Ahmad, Ramsha Narmeen, Muhammad Waleed Aftab, Yazeed Alkhrijah, Mohamad A. Alawad, Aryan Kaushik

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Improving Early Detection of Dementia: Extra Trees-Based Classification Model Using Inter-Relation-Based Features and K-Means Synthetic Minority Oversampling Technique by Yanawut Chaiyo, Worasak Rueangsirarak, Georgi Hristov, Punnarumol Temdee

“…For data balancing, the K-Means Synthetic Minority Oversampling Technique (K-Means SMOTE) was applied to generate synthetic samples in under-represented regions of the feature space, addressing class imbalance. Extra Trees (ET) was used for model construction due to its noise resilience and ability to manage multicollinearity. …”
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Investigation of farmers’ awareness of water conservation and its determinants in arid regions: A case study of the Turpan-Hami Basin by Dongping Guo, Abdugheni Abliz, Yue Kong, Jialin Li, Xianhe Liu, Buasi Nurahmat

“…Farmers are the primary agents of agricultural water conservation, and their awareness of water conservation is a key factor in guiding their behavior and achieving efficient water use, which is particularly vital for ensuring the rational allocation and sustainable utilization of water resources in arid regions. This study used random sampling to assess water conservation awareness among 332 farmers in the Turpan–Hami Basin and systematically analyzed its spatial distribution and key influencing factors using kriging interpolation and a binary logit model. …”
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Determinants of household-level food and nutritional security in urban vegetable producers: A case study by Yusuf UMER, Petros CHAVULA, Mohammed ABDUMALIK, Abdisha Abrahim ADAME, Selahdin AHMED, Eliyas ABDI

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Intelligent intrusion detection system based on crowd search optimization for attack classification in network security by Chetan Gupta, Amit Kumar, Neelesh Kumar Jain

“…We have developed the hybrid model based on crow search optimization (CSO) and random forest (RF) algorithm for identifying threats and irregularities in a computer network. …”
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Spatial expansion of artisanal and small-scale gold mining nearby the Nile River, Sudan and its potential environmental impacts: Insights from Planetscope data and machine learning by Abdelmajeed A. Elrasheed, Yousif Y. Obaid, Szilárd Szabó

“…We aimed to use PlanetScope data to detect and map ASGM and highlight its environmental impacts around the Nile River, North Sudan, using the random forest (RF) classifier in three steps. First, a visual inspection and analysis were performed to evaluate how distinguishable ASGM sites are from rock units/geological features in color composites; then, reference data were collected from processed images for training and testing, and supervised classification was conducted using binary and multiclass RF classifiers. …”
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Effects of phenobarbitone on neonatal hyperbilirubinemia, a systematic review and meta-analysis of randomized controlled trial by Jie Zhang, Bo Zheng, Jianbo Zhuang, Yu Chen, Xiaming Xu, Xinfa Ren

“…Data analysis was conducted using Review Manager 5.3, with mean difference (MD) and 95% confidence intervals (CI) calculated for continuous variables, while risk ratios (RR) were estimated for binary variables. …”
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Real-Time 14-Gbps Physical Random Bit Generator Based on Time-Interleaved Sampling of Broadband White Chaos by Longsheng Wang, Tong Zhao, Daming Wang, Danyu Wu, Lei Zhou, Jin Wu, Xinyu Liu, Yuncai Wang, Anbang Wang

“…An analog-to-digital converter (ADC) chip integrated by two time-interleaved sub-ADCs with a maximum sampling rate of 7 GHz is utilized to discretize the white chaos into parallel binary streams. After real-time interleaving combination and exclusive-OR operation in the field-programmable gate array (FPGA), a 14-Gbps binary stream with verified randomness is achieved.…”
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Two-stage multiple imputation with a longitudinal composite variable by Xuzhi Wang, Martin G. Larson, Chunyu Liu

“…Methods We evaluated the performance of two-stage MI in a novel context, imputing a composite variable constructed from several continuous and binary components in the longitudinal setting while handling missing data due to MAR and missing not at random (MNAR). …”
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Enhancing predictive maintenance in automotive industry: addressing class imbalance using advanced machine learning techniques by Yashashree Mahale, Shrikrishna Kolhar, Anjali S. More

“…The on-board diagnostic dataset utilized has only 16.3% of the failure data, and to address this, 3 key approaches were explored: [i] synthetic minority oversampling technique (SMOTE), [ii] cost-sensitive learning, [iii] ensemble methods. …”
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Accounting for extent of non-compliance when estimating treatment effects on an ordinal outcome in randomized clinical trials by Junxian Zhu, Jialiang Li, A. Mark Richards, Mark Y. Chan, Bee-Choo Tai

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TESTOSTERONE REPLACEMENT THERAPY IN HYPOGONADAL AND ANEMIC ELDERLY MEN: A META-ANALYSIS OF RANDOMIZED CONTROLLED TRIALS by VM Prizão, MM Souza, BAAH Morais, BX Mendes, MLR Defante

“…Review manager was used to perform all statistical analyses. Results: Three RCTs were included, comprising 883 patients, of whom 49.1% were treated with TRT. …”
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Medical insurance-related professionals’ identification of the benefits of the medical insurance system in Northeast China: a cross-sectional study by Zili Zhou, Huan Liu, Linghan Shan, Ye Li, Xin Zhang, Jiahui Wang, Zheng Kang, Mingli Jiao, Yanhua Hao, Yangguang Chen, Qunhong Wu

“…Interviewees were selected using a multi-stage stratified cluster random sampling method. A binary logistic regression model was employed to identify the factors influencing the IBMIS. …”
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Efficacy and safety of agents for IgA nephropathy: a network meta-analysis of randomized controlled trials by Bo Chen, Bo Chen, Yan Zhu, Yang Yang, Gaosi Xu

“…Proteinuria control (36 studies assessing 24-h UPE): The BLyS/APRIL dual-target inhibitor telitacicept (SMD = −5.21, −7.55 to −2.87) and STE + RASI (SMD = −1.98, −3.15 to −0.82) significantly reduced 24-h UPE, outperforming the mycophenolate mofetil combined with steroids regimen (SMD = −0.97, −2.74 to 0.80). …”
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A comparison of modeling approaches for static and dynamic prediction of central line-associated bloodstream infections using electronic health records (part 2): random forest mode... by Elena Albu, Shan Gao, Pieter Stijnen, Frank E Rademakers, Christel Janssens, Veerle Cossey, Yves Debaveye, Laure Wynants, Ben Van Calster

“…Models including multiple outcome events (multinomial and competing risks) display a different internal structure compared to binary and survival models, choosing different variables for early splits in trees. …”
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